Among the numerous TV distribution services, IPTV (Internet protocol TV) is becoming increasingly important and is more and more replacing analogue or non packet based transmission methods. It is a major responsibility of the broadcast provider towards both content provider and customer to maintain the quality of its service. In large IPTV networks only fully automated quality monitoring probes can fulfil this requirement.
In order to achieve a high degree of satisfaction of the user of video services such as non-interactive streaming video (IPTV, VoD) or static video (DVD), the perceived video quality of those services need to be estimated.
To this aim, video quality models are developed which provide estimates of the video quality as perceived by the user. Those models can for instance output the degree of similarity between the video received at the user side and the original non-degraded video. In addition, and more sophistically, the Human Visual System (HVS) can be modelled. At last, the model can map the results of extensive subjective quality tests.
Video quality models and thus measurement systems are generally classified as follow:
Quality Model Types
                Full Reference (FR): a reference signal is required.        Reduced-Reference (RR): partial information extracted from the source signal is required.        No-Reference (NR): no reference signal is required.Input Parameters Types        signal/media-based: the decoded image (pixel-information) is required.        parameter-based: bitstream-level information is required. Information can range from packet-header information, requiring parsing of the packet-headers but not (full- or partial) decoding of the bitstream to the complete decoding of the bitstream.Type of Application        Network Planning: the model or measurement system is used before the implementation of the planning in order to plan the best possible implementation.        Service Monitoring: the model is used during service operation.Related information of the types of video quality models can be found in references [1], [2], or [3].        
In the context of MPEG-based video services, one of the parameters influencing the video perceived quality is the GOP-Structure (GOP=Group of Pictures), including the GOP-length, i.e., the distance between frames which do not require previous or further frames to be decoded, the so-called ‘key-frames’ or “I-frames”. One Group of Picture covers one I-frame and all frames till the next I-frame of the video sequence.
The GOP-structure—and thus GOP-length—is generally chosen as a trade-off between encoding efficiency and error-propagation (see, e.g., references [4], [5], [6]). In these references, the authors provide guidelines for selecting the most appropriate GOP structure for MPEG.
Some models take as input parameters GOP-related parameters but only under packet loss conditions, as in references [2], [7], [8], [9], or [10]. However, they consider only fixed GOP lengths and examine the impact on quality based on the temporal distance of the frame where the packet loss occurs to the next key frame. The quality impact of the GOP-length on encoding is not taken into account.
Quality estimation methods commonly support a distinguished estimation of the quality related to the coding (compression, Qcod) of the video signal and the quality due to packet loss during transmission (Qtrans). Quality estimation methods commonly use one of two approaches to combine an estimation concerning the quality of the compression and the transmission quality. Equation (1) and (2) illustrate the two different approachesQ=Q0−Qcod−Qtrans, Q0,Qx 0 . . . 100  (1)Q=Q0*Qcod*Qtrans, Q0,Qx 0 . . . 1  (2),in which Q0 represents the base quality or a function of the base quality.